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COMED - mission and vision:
COMED is regarded by experts and users as the premier database for gaining reliable, objective data on efficiency
of exposure control measures. COMED users will be able to:
- Compare efficiencies of different control options and identify key performance characteristics
- Use Control Advice Sheets to communicate essential information on control measures to decision makers and end users
- Rely on COMED data to support internal proposals to improve exposure controls
COMED - Advantages:
- A tangible 'product' in the form of the COMED web tool
- 'Self-growing' Web based database with online access to
- Exposure data (incl. 'grey' literature) on control efficiency on common tasks/processes collected together in one convenient source
- Evidence-based, quantified RMM efficiency data as required under REACH
- Control Advice Sheets to encourage proper use of exposure controls and explain key characteristics (positive and negative)
- An authoritative data source with a unique base of qualified occupational hygienists
- All data entries reviewed by experts to ensure accuracy and completeness
Become a part of the COMED community!
COMED – the Control Measures Efficiency Database – was developed out of a joint initiative between BOHS and the Fraunhofer ITEM Institute in Germany started in 2016.
The idea originated from a series of workshops run by Andy Gillies and Alvin Woolley at British Occupational Hygiene Society (BOHS) annual conferences and regional meetings in the UK.
A BOHS Working Group was set up to run the project and this reported annually to the Board (formerly Council) of BOHS, with a final report submitted to the Board meeting in June 2019.
COMED is now managed and run by a Working Group led by Dr Stefan Hahn at the Fraunhofer ITEM Institute in Hannover, Germany.
It was this team that created the database and web tool that forms the heart of COMED.
COMED is a web-based tool using a MySQL database to present information on the proven efficiency of common exposure controls used in a range of activities.
We have defined 'efficiency' as the percentage reduction in exposure when the control measure is properly applied compared to the situation without the control in place.
An additional feature of COMED is the Control Advice Sheets (CAS) which are aimed at users of the control measures and summarise key information from the database in a practical and usable way.
There are currently (November 2021) over 180 data entries covering a range of processes (e.g. welding, grinding, sanding) and control measures (e.g. on-tool extraction, water suppression).
There are two levels of User for the COMED database – Basic and Premium.
A Basic level user can search the database for information on efficiency of different exposure controls for a variety of activities, identify key performance characteristics which affect efficiency, and view relevant Control Advice Sheets.
A Premium level user has all the functionalities of a Basic user, plus they have the ability to create new datasets, and carry out more detailed analysis of data entries.
COMED provides quantitative data on efficiency of individual control measures.
It is not a substitute for a detailed assessment of adequate control of exposure as required under the Chemical Agents Directive.
Measuring and assessing exposure to hazardous substances is a specialist skill requiring training and experience.
It should be carried out by someone with expert knowledge in the field such as a qualified Occupational Hygienist.
COMED is managed and run by a Working Group led by Dr Stefan Hahn at the Fraunhofer ITEM Institute in Hannover, Germany. It was this team which created the database and web tool that forms the heart of COMED.
Currently the team is working to update and improve COMED.
The Management group is responsible for discussion, agreement, and sharing the work on
- maintenance as well as improvements of the database to provide new functionalities work (Database Team), and
- coordination of peer-review and evaluation of the datasets (Data Review Team), and
- design, development and allocation of dataset quality scores as well as creation of control advice sheets (Validation Team).
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